Xu Yang, Yi Liu, Yi Jiang, Hao Wen, Jing Zhang, Jia Chen
{"title":"基于化学分析法的GIS局部放电状态评价","authors":"Xu Yang, Yi Liu, Yi Jiang, Hao Wen, Jing Zhang, Jia Chen","doi":"10.1109/ICHVE49031.2020.9280073","DOIUrl":null,"url":null,"abstract":"In order to use SF<inf>6</inf> decomposition characteristics to assess the partial discharge (PD) degree of DC gas-insulated switchgear (GIS), the authors studied the PD characteristics of the whole process from the initial discharge to the near breakdown of the free conductive particle defect in DC GIS. <tex>$\\pmb{q}_{\\pmb{v}}, \\pmb{n}_{\\pmb{v}}$</tex>, and <tex>$\\Delta \\pmb{t}_{\\pmb{v}}$</tex> are selected as the feature quantities for characterizing the PD state, and the PD severity is divided into three levels. Then, a large number of SF<inf>6</inf> decomposition experiments were carried out under three PD level, and the decomposition characteristics of SF<inf>6</inf> were obtained. The experimental results show that SF<inf>6</inf> decomposition produces include five stable components of CF<inf>4</inf>, CO<inf>2</inf>, SO<inf>2</inf>F<inf>2</inf>, SOF<inf>2</inf> and SO<inf>2</inf>, among which SOF<inf>2</inf> is the most important decomposition product, and the concentration of the remaining four products is close to each other. Finally, it is proposed to use the concentration ratios <tex>$\\pmb{R}$</tex> (CF<inf>4</inf>/CO<inf>2</inf>) and <tex>$\\pmb{R}$</tex> [SO<inf>2</inf>F<inf>2</inf>/(SOF<inf>2</inf>+SO<inf>2</inf>)] as characteristic quantities to study the correlation between SF<inf>6</inf> decomposition components and PD degree. And based on the C4.5 algorithm, a decision tree for the PD degree assessment is constructed with an accuracy rate of 91.67%.","PeriodicalId":6763,"journal":{"name":"2020 IEEE International Conference on High Voltage Engineering and Application (ICHVE)","volume":"90 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"State Assessment of GIS Partial Discharge Based on Chemical Analysis Method\",\"authors\":\"Xu Yang, Yi Liu, Yi Jiang, Hao Wen, Jing Zhang, Jia Chen\",\"doi\":\"10.1109/ICHVE49031.2020.9280073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to use SF<inf>6</inf> decomposition characteristics to assess the partial discharge (PD) degree of DC gas-insulated switchgear (GIS), the authors studied the PD characteristics of the whole process from the initial discharge to the near breakdown of the free conductive particle defect in DC GIS. <tex>$\\\\pmb{q}_{\\\\pmb{v}}, \\\\pmb{n}_{\\\\pmb{v}}$</tex>, and <tex>$\\\\Delta \\\\pmb{t}_{\\\\pmb{v}}$</tex> are selected as the feature quantities for characterizing the PD state, and the PD severity is divided into three levels. Then, a large number of SF<inf>6</inf> decomposition experiments were carried out under three PD level, and the decomposition characteristics of SF<inf>6</inf> were obtained. The experimental results show that SF<inf>6</inf> decomposition produces include five stable components of CF<inf>4</inf>, CO<inf>2</inf>, SO<inf>2</inf>F<inf>2</inf>, SOF<inf>2</inf> and SO<inf>2</inf>, among which SOF<inf>2</inf> is the most important decomposition product, and the concentration of the remaining four products is close to each other. Finally, it is proposed to use the concentration ratios <tex>$\\\\pmb{R}$</tex> (CF<inf>4</inf>/CO<inf>2</inf>) and <tex>$\\\\pmb{R}$</tex> [SO<inf>2</inf>F<inf>2</inf>/(SOF<inf>2</inf>+SO<inf>2</inf>)] as characteristic quantities to study the correlation between SF<inf>6</inf> decomposition components and PD degree. And based on the C4.5 algorithm, a decision tree for the PD degree assessment is constructed with an accuracy rate of 91.67%.\",\"PeriodicalId\":6763,\"journal\":{\"name\":\"2020 IEEE International Conference on High Voltage Engineering and Application (ICHVE)\",\"volume\":\"90 1\",\"pages\":\"1-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on High Voltage Engineering and Application (ICHVE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICHVE49031.2020.9280073\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on High Voltage Engineering and Application (ICHVE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICHVE49031.2020.9280073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
State Assessment of GIS Partial Discharge Based on Chemical Analysis Method
In order to use SF6 decomposition characteristics to assess the partial discharge (PD) degree of DC gas-insulated switchgear (GIS), the authors studied the PD characteristics of the whole process from the initial discharge to the near breakdown of the free conductive particle defect in DC GIS. $\pmb{q}_{\pmb{v}}, \pmb{n}_{\pmb{v}}$, and $\Delta \pmb{t}_{\pmb{v}}$ are selected as the feature quantities for characterizing the PD state, and the PD severity is divided into three levels. Then, a large number of SF6 decomposition experiments were carried out under three PD level, and the decomposition characteristics of SF6 were obtained. The experimental results show that SF6 decomposition produces include five stable components of CF4, CO2, SO2F2, SOF2 and SO2, among which SOF2 is the most important decomposition product, and the concentration of the remaining four products is close to each other. Finally, it is proposed to use the concentration ratios $\pmb{R}$ (CF4/CO2) and $\pmb{R}$ [SO2F2/(SOF2+SO2)] as characteristic quantities to study the correlation between SF6 decomposition components and PD degree. And based on the C4.5 algorithm, a decision tree for the PD degree assessment is constructed with an accuracy rate of 91.67%.